Metabolic profiling of blood plasma in depression in pregnant women during early pregnancy

Objective The study aimed to perform metabolic profiling of serum samples using liquid chromatography with mass spectroscopy (LC-MS) and to explore potential biomarkers of early trimester depression. Method Using the Edinburgh Postnatal Depression Scale (EPDS), participants were randomly divided into study and control groups. Serum metabolic profiles of the two groups were analysed by using LC-MS. Differential metabolite and pathway analysis were identified by using orthogonal projections to latent structure-discriminant analysis (OPLS-DA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Additionally, least absolute shrinkage and selection operator (LASSO) logistic and receiver operating characteristic (ROC) curve analyses were also conducted to explore potential biomarkers of antenatal depression (AD). Results The study included 41 participants, consisting of 16 subjects with AD and 25 controls. A total of 22 different metabolites were identified ( p < .005), mainly affecting glycerophospholipid metabolism, linoleic acid metabolism, synthesis and degradation of ketone bodies, phenylalanine metabolism, and butanoate metabolism. The area under the ROC curve (AUC) for the LysoPC (24:0) was 0.858. This suggests that LysoPC (24:0) may be a potentially effective predictor of risk factors for AD. Conclusions The study suggests that LysoPC (24:0) may be an effective and specific lipid biomarker for early trimester depression.